ABSTRACT
The methods used to train practitioners in a broad range of occupations as distinct from each other as manufacturing to war˜ghting are changing. With reduced training budgets, access to live training has been substantially reduced (Erwin, 2013). Unless other highly effective training options are put in place, it is only a matter of time before losses in knowledge and skill pro˜ciency are experienced. Maintaining a high level of pro˜ciency will require training packages to be systematically designed such that they optimize skill acquisition and retention. The key to accomplishing this is identifying those training options that maximize training transfer. Unfortunately, the data-grounded best practices that can be used to direct the design of training packages to meet this goal are still limited (Burke & Hutchins, 2008). In general, a training package typically commences with classroom training to impart a foundation of declarative knowledge (i.e., general facts, principles, rules, and concepts) and basic skills (Cohn, Stanney, Milham, Jones, Hale, Darken & Sullivan, 2007). Next, trainees are typically provided with a means to apply their newly acquired knowledge and skills and practice to pro˜ciency. This is often done through live training exercises. With the reduction in access to live training, computer-based alternatives to live training can be used to ˜ll this gap. Virtual environments (VE) provide one such alternative.
